The ability to couple cancer patients with genetically-targeted therapeutic strategies remains a major challenge due to the heterogeneous and evolvable nature of individual tumors. This is particularly true of malignant melanoma. Although targeted chemotherapies have improved survival in previously untreatable stages of disease, many melanomas do not contain actionable genetic features; and among those that do, response to treatment is highly variable and often short-lived due to intrinsic and acquired chemoresistance. These resistance patterns are common not only in melanoma, but also develop against nearly all targeted anticancer therapies. Thus, to achieve consistent and durable responses to targeted therapy, it would be highly useful to develop strategies for real-time drug profiling, in which functional therapeutic targets can be identified among diverse and heterogeneous tumors to develop potent anticancer drug combinations. The proposed research project aims to develop a platform for real-time drug profiling of individual melanomas. This work involves two major components. First, we will apply high-throughput functional genomic screens to patient-derived melanoma samples in order to identify therapeutic targets. Next, utilizing a pre-clinical xenograft model derived from whole-tissue melanoma explants, we will develop a strategy to validate these screens as a predictive technology. The proposed work provides an efficient strategy to profile patient-derived melanomas and predict patient responses to therapy. If successful, this could revolutionize the way that cancer patients are diagnosed and linked with anticancer therapies. Despite advances in treatment, less than half of patients treated for stage IV melanoma are alive at one year, and expert guidelines recommend enrollment in a clinical trial for the majority of patients who will ultimately fail approved therapies. Thus, new personalized strategies are urgently needed for the treatment of malignant melanoma. This project is novel in that high-throughput functional genomics will be applied, for the first time, t a large panel of melanoma tissue derived directly from patient biopsies. Pooled shRNA screening offers a rapid platform to identify functional drug targets among diverse and heterogeneous tumors. Drug sensitivity analysis in vivo can then function to validate these screens as a predictive technology, and designate therapies with the highest potential for clinical use. The proposed research project aims to develop a strategy for precise, real-time drug profiling in order to focus and expand personalized therapeutic strategies for patients with malignant melanoma.